Some people refer to Pearson’s r as
a “Pearson product-moment correlation coefficient” so that’s how I’ll refer
to it here. If we were reporting data for our example, we might write a
sentence like this.

“A Pearson product-moment
correlation coefficient was computed to assess the relationship between the
amount of water that one consumed and rating of skin elasticity.”

You want to tell your reader the
value of Pearson’s r so that they can understand the strength of the
relationship between variables. You also might want to tell your reader
whether or not there was a significant difference between condition means.
Recall that some people believe you should report significance when you
conduct a Pearson’s r, but other people don’t feel the same way. I am going
to tell you how to report significance so that we have all our bases
covered. You can report data from your own experiments by using the template
below.

You might want to make reference to
the scatterplot that you created. The you’ll most likely want to put your
scatterplot, and all other graphs, in the Figures section of your APA style
paper. The problem is that no one will know they are in that section unless
you make reference to them in the text. You can use the following template
to reference your scatterplot.

“A scatterplot summarizes the
results (Figure ____)”

In the blank in the above sentence,
you will put the Figure number. If your scatterplot is the only figure that
you are referencing, you can use a 1. Otherwise, use the number that your
scatterplot corresponds with. In our example, we will assume that our
scatterplot is the only figure in the Figures section. For this reason, we
would write the following sentence.

You’ll want to briefly recap in
words that people can understand. Try to imagine trying to explain your
results to someone who is not familiar with science. In one sentence,
explain your results in easy to understand language.

When you put the three main
components together, results look something like this.

“A Pearson product-moment
correlation coefficient was computed to assess the relationship between the
amount of water that one consumed and rating of skin elasticity. There was a
positive correlation between the two variables, r = 0.985, n = 5, p = 0.002.
A scatterplot summarizes the results (Figure 1) Overall, there was a strong,
positive correlation between water consumption and skin elasticity.
Increases in water consumption were correlated with increases in rating of
skin elasticity.”